Goal representation for BDI agent systems

  • Authors:

  • Lars Braubach;Alexander Pokahr;Daniel Moldt;Winfried Lamersdorf

  • Affiliations:

  • Distributed Systems and Information Systems, Computer Science Department, University of Hamburg, Hamburg, Germany;Distributed Systems and Information Systems, Computer Science Department, University of Hamburg, Hamburg, Germany;Theoretical Foundations of Computer Science, Computer Science Department, University of Hamburg, Hamburg, Germany;Distributed Systems and Information Systems, Computer Science Department, University of Hamburg, Hamburg, Germany

  • Venue:
  • ProMAS'04 Proceedings of the Second international conference on Programming Multi-Agent Systems
  • Year:
  • 2004

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Abstract

Agent-oriented system development aims to simplify the construction of complex systems by introducing a natural abstraction layer on top of the object-oriented paradigm composed of autonomous interacting actors. One main advantage of the agent metaphor is that an agent can be described similar to the characteristics of the human mind consisting of several interrelated concepts which constitute the internal agent structure. General consensus exists that the Belief-Desire-Intention (BDI) model is well suited for describing an agent's mental state. The desires (goals) of an agent represent its motivational stance and are the main source for the agent's actions. Therefore, the representation and handling of goals play a central role in goal-oriented requirements analysis and modelling techniques. Nevertheless, currently available BDI agent platforms mostly abstract from goals and do not represent them explicitly. This leads to a gap between design and implementation with respect to the available concepts. In this paper a generic representation of goal types, properties, and lifecycles is developed in consideration of existing goal-oriented requirements engineering and modelling techniques. The objective of this proposal is to bridge the gap between agent specification and implementation of goals and is backed by experiences gained from developing a generic agent framework.